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Probabilistic Diagnosis of Link Loss Using End-to-End Path Measurements and Maximum Likelihood Estimation

Title: Probabilistic Diagnosis of Link Loss Using End-to-End Path Measurements and Maximum Likelihood Estimation.
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Name(s): Sun, Bo, author
Zhang, Zhenghao, professor directing thesis
Li, Feifei, committee member
Duan, Zhenhai, committee member
Department of Computer Science, degree granting department
Florida State University, degree granting institution
Type of Resource: text
Genre: Text
Issuance: monographic
Date Issued: 2009
Publisher: Florida State University
Place of Publication: Tallahassee, Florida
Physical Form: computer
online resource
Extent: 1 online resource
Language(s): English
Abstract/Description: Internet fault diagnosis has attracted much attention in recent years. In this paper, we focus on the problem of finding the Link Pass Ratios (LPRs) when the Path Pass Ratios (PPRs) of a set of paths are given. Usually, given the PPRs of the paths, the LPRs of a significant percentage of the links cannot be uniquely determined because the system is under-constrained. We consider the Maximum Likelihood Estimation of the LPRs of such links. We prove that the problem of finding the Maximum Likelihood Estimation is NP-hard, then propose a simple algorithm based on divide-and-conquer. We first estimate the number of faulty links on a path, then use the global information to assign LPRs to the links. We conduct simulations on networks of various sizes and the results show that our algorithm performs very well in terms of identifying faulty links.
Identifier: FSU_migr_etd-1501 (IID)
Submitted Note: A Thesis submitted to the Department of Computer Science in partial fulfillment of the requirements for the degree of Master of Science.
Degree Awarded: Summer Semester, 2009.
Date of Defense: June 5, 2009.
Keywords: Link Loss DIAGNOSIS, Maximum Likelihood Estimation
Bibliography Note: Includes bibliographical references.
Advisory Committee: Zhenghao Zhang, Professor Directing Thesis; Feifei Li, Committee Member; Zhenhai Duan, Committee Member.
Subject(s): Computer science
Persistent Link to This Record: http://purl.flvc.org/fsu/fd/FSU_migr_etd-1501
Owner Institution: FSU

Choose the citation style.
Sun, B. (2009). Probabilistic Diagnosis of Link Loss Using End-to-End Path Measurements and Maximum Likelihood Estimation. Retrieved from http://purl.flvc.org/fsu/fd/FSU_migr_etd-1501